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An improved temporal clustering analysis method applied to whole-brain data in fMRI study

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机构: [a]Key Laboratory of Nuclear Analysis Techniques, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China [b]Graduate School of the Chinese Academy of Sciences, Beijing 100049, China [c]General Hospital of Chinese People’s Armed Police Forces, Beijing 100039, China [d]Department of Radiology, Xuanwu Hospital, Capital University of Medical Sciences, Beijing 100053, China
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关键词: fMRI temporal clustering analysis (TCA) RTCA whole brain OTCA

摘要:
Temporal clustering analysis (TCA) has been proposed as a method to detect the brain responses of an fMRI time series when the time and location of the activation are completely unknown. But TCA is still incompetent in dealing with the time series of the whole brain due to the existence of many inactive pixels. If only active pixels are considered, the sensitivity of TCA will be improved greatly and it could be applied to the whole brain. In this study, some modifications were made to TCA to remove inactive pixels, and the applicability of the modified TCA to the whole brain was validated with a set of visual fMRI data. Based on the time series of the modified TCA, activations of the whole brain corresponding to the visual stimulation were detected. Compared with the previous TCA, the modified TCA method shows a significant improvement in the sensitivity to detect activation peaks of the whole brain. (c) 2007 Elsevier Inc. All rights reserved.

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出版当年[2006]版:
大类 | 4 区 医学
最新[2023]版:
大类 | 4 区 医学
小类 | 4 区 核医学
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出版当年[2005]版:
Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
最新[2023]版:
Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

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第一作者机构: [a]Key Laboratory of Nuclear Analysis Techniques, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China [b]Graduate School of the Chinese Academy of Sciences, Beijing 100049, China
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通讯机构: [a]Key Laboratory of Nuclear Analysis Techniques, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
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